• Introduces methods for the generation, analysis, and interpretation of data for clinical research. Major topics include the design of surveys, predictive models, randomized trials, clinical cohorts, and analyses of electronic health records. Prepares students to formulate well-defined research questions, design data collection, evaluate algorithms for clinical prediction, design studies for causal inference, and identify and prevent biases in clinical research. Emphasizes critical thinking and practical applications, including daily assignments based on articles published in major clinical journals and the discussion of a case study each week. Trains students to comprehend, critique, and communicate findings from the biomedical literature. Familiarity with regression modeling and basic statistical theory is a prerequisite. Only HST students may register under HST.194, graded P/D/F. Enrollment limited; restricted to medical and graduate students.

• Textbook Information

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